Search Results for author:
Found 11 papers, 0 papers with code
emoDARTS: Joint Optimisation of CNN & Sequential Neural Network Architectures for Superior Speech Emotion Recognition
This study presents emoDARTS, a DARTS-optimised joint CNN and Sequential Neural Network (SeqNN: LSTM, RNN) architecture that enhances SER performance.
Ranked #1 on
Speech Emotion Recognition
on MSP-IMPROV
Revealing Emotional Clusters in Speaker Embeddings: A Contrastive Learning Strategy for Speech Emotion Recognition
In order to leverage this information, we introduce a novel contrastive pretraining approach applied to emotion-unlabeled data for speech emotion recognition.
Versatile Audio-Visual Learning for Handling Single and Multi Modalities in Emotion Regression and Classification Tasks
This study proposes a \emph{versatile audio-visual learning} (VAVL) framework for handling unimodal and multimodal systems for emotion regression and emotion classification tasks.
Ranked #1 on
Video Emotion Recognition
on CREMA-D
Mixed-EVC: Mixed Emotion Synthesis and Control in Voice Conversion
To achieve this, we propose a novel EVC framework, Mixed-EVC, which only leverages discrete emotion training labels.
Driving Anomaly Detection Using Conditional Generative Adversarial Network
The experimental results reveal that recordings annotated with events that are likely to be anomalous, such as avoiding on-road pedestrians and traffic rule violations, have higher anomaly scores than recordings without any event annotation.
Unsupervised Personalization of an Emotion Recognition System: The Unique Properties of the Externalization of Valence in Speech
A practical approach to improve valence prediction from speech is to adapt the models to the target speakers in the test set.
The Ambiguous World of Emotion Representation
A key reason for this is the lack of a common mathematical framework to describe all the relevant elements of emotion representations.
End-to-end Audiovisual Speech Activity Detection with Bimodal Recurrent Neural Models
Recent advances in audiovisual speech processing using deep learning have opened opportunities to capture in a principled way the temporal relationships between acoustic and visual features.
Speech-Driven Expressive Talking Lips with Conditional Sequential Generative Adversarial Networks
Subjective evaluations show significantly better results for this model compared with the CSG model when the target emotion is happiness.
Human-Computer Interaction
MSP-IMPROV: An Acted Corpus of Dyadic Interactions to Study Emotion Perception
The paper also provides the performance for speech and facial emotion classifiers.
